Complex multiple introductions drive fall armyworm invasions into Asia and Australia

The fall armyworm (FAW) Spodoptera frugiperda is thought to have undergone a rapid ‘west-to-east’ spread since 2016 when it was first identified in western Africa. Between 2018 and 2020, it was recorded from South Asia (SA), Southeast Asia (SEA), East Asia (EA), and Pacific/Australia (PA). Population genomic analyses enabled the understanding of pathways, population sources, and gene flow in this notorious agricultural pest species. Using neutral single nucleotide polymorphic (SNP) DNA markers, we detected genome introgression that suggested most populations in this study were overwhelmingly C- and R-strain hybrids (n = 252/262). SNP and mitochondrial DNA markers identified multiple introductions that were most parsimoniously explained by anthropogenic-assisted spread, i.e., associated with international trade of live/fresh plants and plant products, and involved ‘bridgehead populations’ in countries to enable successful pest establishment in neighbouring countries. Distinct population genomic signatures between Myanmar and China do not support the ‘African origin spread’ nor the ‘Myanmar source population to China’ hypotheses. Significant genetic differentiation between populations from different Australian states supported multiple pathways involving distinct SEA populations. Our study identified Asia as a biosecurity hotspot and a FAW genetic melting pot, and demonstrated the use of genome analysis to disentangle preventable human-assisted pest introductions from unpreventable natural pest spread.


Results
Strain assessment. We did not detect any C-strain individual following analysis of 138 fully assembled mitochondrial DNA genomes (mitogenomes) from Australian samples. Our results, particularly that from Northern Territory, are not dissimilar to the finding of Piggott et al. 56 who detected only two (i.e., 4.2%) C-strain mtCOI haplotype individuals from a much larger (i.e., n = 48) Northern Territory sample size. Proportions of C-strain to R-strain also varied significantly across the different SEA populations (Table S1) in contrast to the patterns observed in China, India, and African nations (e.g., 22,33,34,39,57 ). All Australian populations analysed for their corn or rice mitochondrial haplotypes via mitogenome assemblies of whole genome sequencing data therefore contrasted with the invasive populations from SEA where in some countries (e.g., Myanmar, Vietnam) FAW with the C-strain mtCOI haplotypes made up approximately 50% of the populations examined (see Table S1 for C-and R-strains mitogenome proportions, see also Fig. 1 'C-strain' and 'R-strain' Maximum Likelihood cladograms).
Mutations in the Triosephosphate isomerase (Tpi) gene used to differentiate the C-and R-strains suggested that virtually all individuals from the SEA, PA, and South Korean (i.e., EA) carried the C-strain genotype at the Tpi gene. Of all SEA and PA individuals assessed, none was homozygous for the rice allele at this locus, while a number of samples (n = 10) were heterozygous C-/R-strains, primarily from the Philippines as well as one sample each from Malaysia and South Korea. Similar to the conclusions of Zhang et al. 34 , at least in the invasive range, our finding suggested that the Tpi is not a useful marker: not only are the majority of samples of 'corn' preference, with limited evidence of hybrids and therefore contrasting greatly with whole genome analysis, but both the Tpi Nuclear SNP phylogenetic analysis. Maximum Likelihood (ML) phylogenetic analysis of the global S. frugiperda populations based on 870 neutral single nucleotide polymorphic (SNP) markers provided evidence of complex genetic relationship especially between individuals representing the invasive populations (Fig. 2).

Figure 1.
Maximum Likelihood cladograms of unique Spodoptera frugiperda C-strain and R-strain partial mitochondrial genomes based on concatenation of the 13 PCGs (11,393 bp) using IQ-Tree with 1000 UFBoot replications. Individuals in clades I, II, III, and IV (C-strain) and in Clades I, II, V (R-strain) that are in the same colour scheme (i.e., green, orange, blue, or pinks) shared 100% nucleotide identity. Mitogenome haplotypes from native individuals for both C-and R-strains are in khaki green colour. Red and dark grey dots at branch nodes represent bootstrap values of 87-100% and 74-86%, respectively. Bootstrap values < 74% are not shown. Red arrows indicate invasive individuals' mitogenome haplotypes that are nested within native individuals. Country and sample codes are listed in Tables S1 and S2. www.nature.com/scientificreports/ While the New World native populations (USA, Puerto Rico, Guadeloupe, Mexico, French Guiana, Peru, Brazil) clustered together and shared a basal (ancestral) lineage, the invasive populations did not identify Africa as the founding invasive population nor support the axiom of rapid west-to-east spread across the Old World. Selected individuals from Uganda and Benin appeared to cluster close to China/India populations, but there was no strong bootstrap support for a shared common ancestor (i.e., bootstrap value < 74%). China populations (i.e., CY, YJ, XP from Yunnan; see Fig. 1B in 58 ) formed two closely related sister clades with long branch lengths, suggesting these likely represented separate introduction events. Based on analyses of nuclear SNP data, the main Australian FAW population clade consisted of multiple sister clades and were clustered with varying degree of bootstrap support values. Some of these Australian populations appeared to share close relationship with the FE (i.e., South Korean) population (> 87-100% bootstrap support; e.g., selected Burdekin individuals), while others had largely unknown invasive origin(s). Southeast Asian countries (i.e., Malaysia, Philippines, Laos PDR, Vietnam, Myanmar) and Pacific/Australia (i.e., PNG) have populations that were mixed, and interestingly were ancestral to East African populations (i.e., Malawi, Uganda), while some Australian populations (i.e., NSW; NT) were shown to be closely related to these SE Asian populations with strong bootstrap support (e.g., > 87-100% support for NT and NSW populations). Myanmar and China appeared to not share FAW populations with similar SNP profiles despite being neighbours. Multiple introductions of FAW with diverse genetic profiles and potentially similarly diverse origins were therefore likely the main reason for their wide spread detection across the Old World.
Clear evidence of multiple introductions can therefore be seen from the phylogenetic analysis, with unique introduction events likely underpinning the establishment of FAW populations in EA. (e.g., China) and SEA (e.g., Malaysia). In Australia, while the NT/NSW populations shared closer evolutionary relationships with SE Asian populations, the population origin for most of Qld and WA populations was unclear, and could be due to a sampling effect (e.g., this study could not source FAW populations from e.g., Indonesia, Cambodia, Thailand, Sri Lanka, Bangladesh, etc.). Some Burdekin and South Korean individuals appeared to share closer evolutionary lineage, although the factor leading to this detected pattern remained as yet unknown.  Table 1. Nucleotide diversity (π) varied across a narrow range with the lowest (0.237) being from the Malaysian Kedah State population (i.e., reflected its lab-colony background), and the highest from the Malawian population (0.324), similar to that reported ( 33 ; π = 0.279-0.329) in native and invasive populations based on the same set of 870 SNP loci. The high nucleotide diversity estimates from the SEA, Australia and South Korean populations likely reflected effects of limited (i.e., 870) highly polymorphic SNPs from noncoding genomic regions being used, and are comparable to the findings from Tay et al. 33 that used the same sets of SNP loci. We did not detect significant overall differences between the various invasive populations, and for the SE Asian and Australian populations the nucleotide diversity estimates were generally between 0.258 and 0.291. All invasive populations from Africa (Benin, Malawi, Uganda), SA/EA (India, China (CY, XP, XJ), South Korea), SEA (Malaysia (Johor, Kedah, Penang), Laos, Vietnam, Myanmar, Philippines), and Pacific (PNG)/Australia (WA (Kununurra), NT, QLD (Strathmore, Walkamin, Burdekin), NSW (Wee Waa)) showed higher average observed heterozygosity (Het obs ) than the average expected heterozygosity (Het exp ), with the highest Het obs seen in the Malawian population as also reported previously 33 . Within the Australian populations, highest average observed heterozygosity was seen in the Strathmore population, while in populations in SEA (i.e., Myanmar, Philippines) and the EA (i.e., South Korea) all showed similar average Het obs . Negative average F IS values for all populations were consistent with Het obs being higher than Het exp , and suggested populations were out-breeding (i.e., avoidance of matings between related individuals; 59 ). Similar to the previous findings 33 , the lower Het exp (i.e., Het obs > Het exp ; see 60 ) could likewise indicate recent mixing of distinct populations from SEA that suggest multiple introductions (e.g., 33,39 cf. 46,47,61,62 ; i.e., due to a recent bottleneck from a recent western Africa founder event). The observed heterozygosity excess detected in all invasive range populations could be further explained as due to population sub-structure and isolation breaking through periodic migration. Significant numbers of loci (ca. 30%) were also shown to not be in Hardy-Weinberg equilibrium (HWE) especially for the Malaysian (i.e., Kedah), but also Australian (i.e., Wee Waa, NT, Kununurra), Chinese (e.g., XP), South Korean, and Malawian populations. Taken as a whole, genetic diversity results from this study therefore suggested that the invasive Asian (i.e., SA, SEA, EA) FAW populations exhibited signatures of recent mixing of previously separated populations. Simulated patterns of moth migration of various invasive FAW populations such as between Myanmar and China  Table S1 and "Material and methods" section for population details and statistical calculation approach. Refer to 33 for details of African and Asian FAW populations.  www.nature.com/scientificreports/ (e.g., 41,42,55 ) and to Australia 54 are incompatible with the population genomic data, which suggests these were likely discrete and non-panmictic FAW populations with the most probable explanation being due to multiple origins of founding populations.

Genetic differentiation analysis. Estimates of pairwise genetic differentiation (F ST ) between populations
varied significantly (Table 1) and extended to between populations within a country (e.g., Mackay vs. rest of Australia; Kedah vs. rest of Malaysia). Of interest are the pairwise estimates between different Australian FAW populations from Kununurra (Western Australia), Northern Territory, Queensland (Strathmore, Walkamin, Burdekin, Mackay) and New South Wales (Wee Waa) that represented the most recently reported invasive populations in this study, and predominantly showed significant differentiation amongst themselves (with the exception of the two Queensland populations of Mackay and partially for Walkamin) and with other SEA/SA/ EA countries. The majority of non-significant population genetic differentiation estimates were in SEA where the presence of FAW was reported earlier, i.e., since 2018 (e.g., 63,64 or as early as 2008 65,66 ; see also 33 ), while across Asia (e.g., China) since 2016 but also potentially pre-2014 ( 16,67 ; see also 33 ). Interestingly, significant genetic differentiation was observed between populations from Yunnan province in China and populations from Myanmar, Laos, and Vietnam. Penang and Johor (Malaysia) populations were not significantly differentiated from other SE Asian populations, nor with Ugandan and Malawian populations from east Africa. Individuals from Benin and Mackay (Queensland, Australia) showed non-significant genetic differentiation with all populations except with Kedah, and for Mackay also surprisingly with the Wee Waa population from New South Wales. The South Korean population exhibited significant genetic differentiation with SE Asian population except with Mackay, India and the Yuanjiang (YJ) population in Yunnan Province. Finally, the Kedah population, being one of the earliest collected samples from Malaysia and having been maintained as a laboratory population, showed strong differentiation with all populations (and lowest nucleotide diversity, π = 0.237; Table 2) further supporting unique, non-African, introduction events in SEA. Strong genetic differentiation suggested there was limited gene flow to breakdown sub-structure between populations, and the F ST estimates from these invasive populations therefore failed to support a west-to-east spread pathway for the FAW.  33 . Nucleotide diversity: (Nt Div, π); Avg. Het exp , average expected heterozygosity; Avg. Het obs , average observed heterozygosity; Avg. Hom exp , average expected homozygosity; Avg. Homt obs , average observed homozygosity; % HWE, per centage loci in Hardy-Weinberg Equilibrium; F IS , inbreeding coefficient. Refer to Table S1 and "Material and methods" sections for population details and how the statistics were calculated. www.nature.com/scientificreports/ This observation instead suggested the widespread presence of genetically distinct FAW populations, likely due to independent introductions and therefore also highlighting likely biosecurity weaknesses especially in East Asia (e.g., China, South Korea) and SEA (e.g., Malaysia). The genetic diversity of Australian populations identified surprisingly complex sub-structure patterns given the short time frame of population detections across different northern Australian regions. Significant genetic differentiation between, e.g., Kununurra (WA), Northern Territory (NT), Queensland (e.g., Strathmore, Burdekin), and Wee Waa (NSW) populations suggests these populations likely derived from separate establishment events. The WA Kununurra population was not significantly differentiated from the Johor State (Malaysia), India and the Cangyuan (CY) China populations, suggesting a potential south-eastern route from SA/SEA into north-western Australia. Contrasting this, Walkamin and Mackay populations showed non-significant genetic differentiation with the Madang (PNG) population, suggesting a potential second pathway for SEA individuals to arrive at the north-eastern region of Australia. Significant genetic differentiation between WA, NT, and Qld populations suggested that at least during the early stage of pest establishment in northern Australia, there was limited gene flow to homogenise the unique genetic background carried by these distinct individuals, some of which exhibited also distinct insecticide resistance profiles 48 Fig. 3d between China, Malaysia (Kedah State), and Australia (NT, NSW)). Genetic variability between Australian populations (e.g., Strathmore (QLD) vs. NT and NSW) was also evident (Fig. 3d).
PCA also showed that differences existed between FAW populations from the Madang Province in PNG and with the Strathmore population from Qld (Fig. 3e). The SEA FAW populations from Lao PDR/Vietnam also exhibited diversity from the South Korean population (Fig. 3f), with the South Korean and Strathmore populations largely exhibiting similar diversity patterns, while the Madang population shared similarity with Laos and www.nature.com/scientificreports/ Vietnam populations. Plotting all SEA populations against China clearly showed that populations from SEA were distinct from the Chinese FAW populations (Fig. 3g), while in Australia, individuals from various populations shared similarity with both Chinese and SEA FAW. Despite the connectedness of the landscape between SEA and China, SEA largely appeared to have their own FAW populations, with FAW in SEA and in China differing in their genome compositions overall as shown via PCA. PCA further enabled visualisation of genetic diversity amongst Australia FAW populations, suggesting that arrival and establishment of FAW likely involved separate introduction events that followed closely after each other and over a short timeframe. While it had been anticipated that the southward spread of FAW from SEA would necessarily lead to Australia FAW and PNG FAW to share similar genetic backgrounds, the Madang Province FAW population appeared to be different from the Strathmore (Qld) population, with the Madang population being more similar to Lao PDR/Vietnam populations, and the Strathmore population more similar to FAW from South Korea.
DivMigrate analysis. Directionality of gene flow between African, South Asia (Indian), East Asia (China) and SE Asian populations were predominantly from China to east African and SE Asian populations (e.g., Figs. 4a, b, S-1; see also Table 3), while movements of FAW in Laos and Vietnam (i.e., the Indochina region) were predominantly with other SEA countries (e.g., with Myanmar and East Africa; Figs. 4c, d, S-2; see also Table 3) but with no directional movements to the three Yunnan populations (CY, XP, YJ). Migration directionality with other SE Asian populations (e.g., Johor (JB; Fig. S-3) and Penang (PN, Fig. S-4)) showed that these two populations (but especially the Johor population) were predominantly source populations for Uganda, Malawi, Philippines, Vietnam, and PNG ( Fig. S-3). Bidirectional migration between Myanmar and Laos PDR populations were also detected with the Johor population from Malaysia ( Admixture analysis. Admixture analyses involving all Australian, Southeast Asian and South Korean populations from this study; and native populations from the Americas and Caribbean Islands, and invasive populations from Africa (Benin, Uganda, Malawi), India, and China 33 , provided an overall complex picture of population structure that reflected the species' likely introduction histories across its invasive ranges.
Admixture analysis that excluded New World, African and Indian populations identified four genetic clusters (i.e., K = 4) to best describe these invasive populations from SEA, and EA (i.e., China, South Korea), and Pacific/ Australia (Fig. 5a). At K = 4, Australian populations from NT and NSW, YJ population from China, South Korean, and Malaysia's Kedah population, each showed unique admixture patterns (i.e., some individuals from NT and NSW populations lacked cluster 3; most of YJ (but also some CY and XP) individuals lacked clusters 1 and 2; South Korean (e.g., MF individuals) lacked cluster 2; Malaysia's Kedah population lacked evidence of admixture (i.e., reflecting its laboratory culture history) and was made up predominantly by individuals that belonged to cluster 4. Populations from China also differed from most populations from SEA due to the overall absence of genetic cluster 4. Taken as a whole, establishment of the FAW populations in China, Malaysia, vs. other SE Asian populations, and between Australian populations (e.g., NT/NSW cf. WA/Qld), likely involved individuals from diverse genetic background (i.e., multiple introductions). At K = 4, the majority of Australian populations appeared to contain genetic clusters similar to China (i.e., cluster 3) and to SEA (i.e., cluster 2).
Overall admixture patterns at best K = 4 in China and SEA remained unchanged when analysed together with African and Indian individuals ( Fig. 5b; excluded Australia). Benin individuals were either similar to China or to SEA, while eastern African populations (e.g., Uganda, Malawi) were similar to Southeast Asian populations from e.g., Vietnam, Laos, and is in agreement with the phylogenetic inference (Fig. 3) that identified these African individuals as having loci that were derived from Southeast Asian populations.
Genome-wide SNP loci demonstrated that invasive FAW populations from SEA and Australia exhibited admixed genomic signatures similar to that observed in other invasive populations 33,34 . While the current invasive populations in Africa and Asia likely arrived already as hybrids as suggested by Yainna et al. 68 , the Malaysia Kedah State population was potentially established by offspring of a non-admixed female. Distinct admixture patterns in Malaysian FAW populations between Kedah and Johor/Penang states therefore suggested that establishment of these populations was likely as separate introduction events. As reported also in Tay et al. 33 , the Chinese YJ population appeared to have admixed signature that differed from XP and CY populations, and suggested that the YJ population could have a different introduction history than the XP and CY populations. Similar multiple genetic signatures based on lesser nuclear markers by Jiang et al. 39 also supported likely multiple introductions of China Yunnan populations.

Discussion
In this study, we demonstrated through genomic analysis of genome-wide SNP markers signatures of multiple independent introductions of S. frugiperda in Asia (i.e., SEA. EA), the detection of distinct population sub-structures between what had been widely assumed (e.g., 41,42,55 )  www.nature.com/scientificreports/ highlight the need to infer population movements through genome-wide analyses; while critical assessments are needed of conclusions based on movement studies such as reverse trajectory analyses 54,55 , and inference of population genetics relying solely on detection reports and limited (e.g., partial mitochondrial genes; partial TPI gene) DNA markers. Importantly, the study demonstrated the unexpected complexity of FAW populations across its current sub-Saharan, South Asia, Southeast Asia, East Asia, and Pacific/Australia invasive ranges since the species' initial 2016 confirmation in western Africa. Results from this study further supported that human (anthropogenic)-assisted activities were likely major contributing factors, as also cautioned by Early et al. 7 based on the prevailing opposite wind direction (i.e., east-to-west) in the African continent. The rapid spread rate of this pest since 2016 to over 70 countries 69 has generally been regarded as a result of its long distance migration ability (e.g., 28,29,40,57 ) following a single introduction into west Africa 19,21,46,47,62 and subsequent wind-assisted dispersal 37 . In contrast, genomic (e.g., 33,38 , and genetic 39,48 ) evidence has begun From the analyses presented here, we suggest that the number of independent introductions of FAW is likely underestimated. For example, while our genomic analyses have identified populations in Malaysia, South Korea, and China 16,33 with distinct signatures, Jiang et al. 39 identified six separate genetic signatures in populations from southern and northern China, and Schlum et al. 38 and Tay et al. 33 identified a total of at least four separate introductions in African populations (e.g., Kenya, Benin, Uganda, Malawi). Population genetic analyses based on limited partial gene markers have also identified low frequencies of unusual polymorphism patterns in the Tpi and mtDNA gene markers in some African and an Indian FAW (e.g., 47,62,71,72 ). Similarly, Gui et al. 40 also detected signatures suggestive of independent introductions based on genome wide SNP analyses but have nevertheless maintained the African origin theory. While the conclusions by these authors have reinforced the hypothesis of the west-east movement of FAW, increasing whole genome evidence makes it more reasonable to conclude that these earlier single gene findings were also evidence of multiple unrecognised independent introductions.
Our investigation based on previously described genome-wide neutral SNP markers 32 enabled integration of the published dataset (i.e., of native New World FAW populations and invasive African, Indian, and Chinese FAW populations) with the current SE Asia, East Asia, and Pacific/Australia FAW populations to reveal a complex picture of the pest's invasive history. While multiple introductions especially in the Asian continent (e.g., China, Vietnam, Malaysia; 16,32,33,39,40,65,66 ; this study) have played an important role leading to the perception of rapid spread, introductions from elsewhere have also contributed to the African establishment and expansion. Further to genomics evidence, resistance allele characterisation and bioassay experiments have also identified invasive populations with non-overlapping unique insecticide resistance profiles in China (e.g., 73 ), Indonesia 74 , Australia 48,49 , India 75 , and Africa 76,77 .
Multiple independent introductions of invasive agricultural pests are well-documented such as for the cryptic whitefly Bemisia tabaci MED and MEAM1 species (e.g., 3,10,78 ), and for the related noctuid pest Helicoverpa armigera (e.g., 1,5,28 ), and underpinned the perceived rapid spread (e.g., 79 ) of these pests in their introduced habitats. Early confirmation of invasive pests in novel habitats is also often challenging especially if initial population sizes were small. For example, while the initial detections of H. armigera in Brazil was during the cropping seasons of 2012/2013 13,80 , its presence in Brazil was only subsequently confirmed to be at least as early as in 2008 81 and potentially earlier elsewhere (e.g., in Peru) in the South American continent 5,82 . Similarly for the FAW, its presence   19 . In Uganda, farmer surveys 84,85 showed that FAW damage symptoms on maize crops were first identified in the Namutumba (since 2013) and the Kamuli (since 2014) districts, while Otim et al. 86 reported farmers observed FAW damage symptoms in eastern and northern Uganda since 2014, although farmers at the time were unaware of this highly invasive exotic armyworm species. Findings of field surveys [84][85][86] were in agreement with anecdotal observations and with single-gene response on Bt maize in South and East Africa, that the FAW could have been present in Africa several years prior to its confirmation in West Africa 70 . While the current FAW populations in Vietnam were shown to have a gene flow directionality from Malaysia, whether this could be linked to the 2008 report 65,66 of outbreaks around Hanoi remained to be answered. Malaysian populations from Penang and Johor States were also shown to be linked to, and potentially source populations for, Ugandan and Malawian FAW populations (Figs. 2, S3, S4), in addition to the earlier results that also showed Chinese FAW populations to be potential source populations ( 33 ; also Fig. 4a, b). Our study and that of Jiang et al. 39 therefore identified two potential biosecurity weakness hotspots in Asia that have contributed to the spread of FAW in recent times. The study of Jiang et al. 39 as well as the studies of Tay et al. 33 and Gui et al. 40 therefore identified at least eight unique genetic/genomic signatures of introduction events across different regions (e.g., southern and northern regions) in China. While reverse trajectory studies by, e.g., Wu et al. 55 that suggested Yunnan province FAW to have originated from Myanmar, results from the present study showed that there was very little genetic connectivity between them (e.g., Fig. 3a), while DivMigrate analysis showed that gene flow directionality was more likely to be from Cangyuan (CY) to Myanmar (Fig. 4a), thereby highlighting the importance of incorporating genomic analyses to aid interpretations of pest movements.
Southeast Asian and Pacific/Australia countries such as Laos, Myanmar, Vietnam, Philippines, Malaysia, and PNG, appeared to be the geographic 'genetic melting pot' for the invasive FAW based on our analyses (Figs. 4a-d; S1-S6), although their population establishment scenarios were different. For example, our analyses suggested that Laos, Myanmar, Philippines, and PNG populations were likely linked to 'bridgehead invasive founder China's CY population' , the Vietnam population was more likely associated with individuals from Malaysia's Johor State 'bridgehead invasive founder population' (Fig. 4c). DivMigrate analyses therefore suggested that populations in these SE Asian countries have diverse origins, both as potential direct recipients of New World FAW (e.g., www.nature.com/scientificreports/ Malaysia, also China) and as recipients of successfully established secondary invasive populations (e.g., Laos, Vietnam, Myanmar), with subsequent bi-directional movements between these countries. Pest spread into Australia originating from Asia and SEA have been shown to be associated with wind patterns 87 , and separate introduction pathways for Western Australia and Queensland insect populations (e.g., the blue tongue virus vector Culicoides brevitarsis) have been reported 88 . Similarly, arrival and subsequent detection of S. frugiperda populations across the northern region of Australia also likely represented separate establishments based on nuclear SNP analysis but did not support the reverse trajectory simulation findings of Qi et al. 54 . Populations between WA, NT, and Qld were shown to be genetically differentiated, suggesting limited gene flow between these populations at the early stage of invasions. The Kununurra population was found to be less genetically differentiated with the Johor (Malaysia) population (but also the population from India), suggesting a route moving south-east from South Asia/SE Asia into Western Australia, potentially via Indonesia. The PNG population was shown to be not significantly differentiated from the Walkamin (Qld) population, while gene flow directionality analysis linked Yunnan populations (e.g., CY (Fig. 4a) and XP (Fig. 4b)) with the PNG population.
Boaventura et al. 74 showed that Indonesian FAW individuals have unique insecticide resistance alleles for the AChE and VGSC genes. In China, Lv et al. 73 reported diamide resistance alleles in individuals from Guangxi and Guizhou Provinces. While this study failed to source Indonesian and Cambodian populations (due to the difficulty of sharing and sending biological material from Indonesia and Cambodia to Australia), significant differences in resistance to indoxacarb was nevertheless detected between WA (Kununurra) and Qld (Strathmore) populations 48,49 , and could be due to the different source populations for the WA and the Qld populations. Ongoing studies to monitor for potential arrivals of novel resistance alleles and those already reported in Indonesia and China to Australia will therefore be needed to inform and impact future FAW management strategies.
Phylogenetic analyses using both mitochondrial genomes and nuclear SNP loci supported multiple introductions at different scales. At least 12 C-strain mitochondrial genomes based on concatenated PCGs were identified, with some mitochondrial DNA genomes being detected only in SEA populations (e.g., Lao03 in Clade II, Lao12 in clade III). In the R-strain, at least 19 unique mitochondrial DNA genomes were detected (Fig. 1). Interestingly, and despite Australia representing the country with the most recent history of FAW's incursions in this study, unique Australian mitochondrial DNA genomes not reported elsewhere in our other invasive populations were nevertheless detected (e.g., S3_Sf20-1 (Clade 1), KB1_107_AusRice (Clade III), 03_SF20-5_rice (Clade IV), 52_Sf20-1_Block2_21 (Clade V), and 55_Sf20-1_Block2_24 (Clade IX)). Some of these unique Australian mitogenomes shared close maternal evolutionary lineage with South Korean individuals (e.g., Clade III) that was further supported by nuclear SNP phylogeny (Fig. 2). Whether this represents linked anthropogenic-assisted invasion history remained to be confirmed, although direct flight by adult moths between the two countries would be unlikely due to the large distance (ca. > 7000 km). Regardless, it highlights the challenge faced by biosecurity agencies globally in preventing accidental introductions of alien species.
An important finding from this study has been that the SE Asian populations were largely clustered away from other Asian (i.e., China, Indian) populations, supporting separate establishment histories of S. frugiperda populations in this region, and demonstrating the role played by independent, potentially anthropogenic-assisted introductions. The date of S. frugiperda's establishment in China and SEA (e.g., Myanmar, Vietnam), though unknown, is potentially as early as pre-2014 ( 67 ; see also 16,33,65,66 ) and populations from SEA and China remained largely separate at least as recently as 2019/2020, based on analysis of our 870 SNP loci (see also 39 based on microsatellite DNA markers), contradicting the hypothesis of a Myanmar origin for the Yunnan S. frugiperda population 41,42,55 . Taken as a whole and incorporating population substructure (i.e., F ST ) analysis, directional migration analysis of invasive S. frugiperda populations identified East Asia (e.g., China, South Korea) and SEA as biosecurity hotspots, while multiple introductions involving genetically distinct S. frugiperda likely occurred in north-western (i.e., Kununurra, WA) and north-eastern (i.e., Burdekin, Qld) Australia.
Population genomic studies via whole genome sequencing have enabled the spread patterns of this invasive pest to be re-evaluated to reveal highly complex scenarios that were likely associated with, or at least initiated by, trade activities. Whole genome sequencing is therefore proposed herein as essential for future biosecurity monitoring, in order to allow population genomics to directly impact on development of management policies and strategies (e.g., 58 ), and to provide practical information to regulators and to some extent producers on how best to manage new invasive populations. The use of genome-wide SNP loci obtained via whole genome sequencing has enabled the elucidation of pathways to disentangle origins and establishment histories. This, bolsters risk assessment efforts, and provide information to biosecurity agencies and to international inter-governmental agencies to differentiate between natural and human-assisted spread. While it would be unlikely to stop natural migration of pests, accidental introductions via human-assisted spread are preventable. Findings from this study set the precedent that aims to inform biosecurity agencies and policy makers to effect behavioural change in the case where pest establishment and spread were underpinned by poor phytosanitary practices.

Material and methods
FAW specimens for genomic analyses. Spodoptera frugiperda populations from the East Asia (i.e., South Korea), Southeast Asia (SEA; i.e., from: Myanmar, Laos, Vietnam, Malaysia, Philippines), and Pacific/ Australia (i.e., Papua New Guinea, and Australia (representing new invasive range by S. frugiperda)) were surveyed for whole genome sequencing (Table S1; Fig. 6). Methods of specimen preservation involved collection of larvae/adults from fields were identical and involved placing specimens directly into highly concentrated ethanol (95-99.9%) and storing at − 20 °C until being used in DNA extraction. Samples sent to CSIRO from Queensland (CSIRO code: Sf20-1) and Western Australia (CSIRO code: SF20-4) were first used for bioassays purpose 48,49 prior to being stored at -20˚C (once laboratory colonies were established) for DNA extraction pur- Processing of genome sequences. Genome sequencing data for each individual were trimmed to remove adapter sequences using Trim Galore! (v 0.6.6; https:// www. bioin forma tics. babra ham. ac. uk/ proje cts/ trim_ galore/) and aligned to the S. frugiperda rice genome (v1.0) 89 using bwa_mem2 (v2) 90  In the population genomic analysis, native FAW populations were excluded as the implication of multiple introductions that resulted in the establishment of Old World invasive FAW populations (e.g., 32,33,38 ) meant that inclusion of our limited native populations (i.e., from eight native localities) vs. the higher number of invasive FAW populations (i.e., from 13 invasive countries) were unlikely to provide greater certainty to detect potential origins of invasive populations. The study therefore uses 452 samples with an average sequencing depth of 19.24 (min. 8.71; max. 56.61; median 17.55) for evolutionary genomic interpretations relating to the gene flow patterns of the global FAW populations. Detailed description of the methods has been provided 32,33 . Admixture was run using multiple K values (3-9), and the cross-validation error (CV) was quantified for each K. The K value with  Table S1). Native New World populations (not shown) and invasive populations from Benin, Uganda, Tanzania, Malawi, India, and China have been reported in Tay et al. 33 . Geographic regions of the sampled countries were as defined by World Atlas and are provided in Table S1. The map was created by importing the colour-formatted map region from MapChart < https:// www. mapch art. net > into Microsoft PowerPoint for Mac v16.54 where location details were added and further manipulated and formatted. Mitochondrial Genome (mitogenome) analysis. The mitogenomes of all individuals from SEA (n = 94), East Asia (South Korea, n = 12), and Pacific/Australia (n = 164) were individually assembled following the approach as described in Tay et al. 33 . Briefly, we used Geneious 11.1.5 to map raw sequences for each FAW individual against a reference genome (GenBank accession number MT897262 (for mtCOI C-strain)/ MT897275 (for mtCOI R-strain); 33 ), followed by fine-tuning to resolve regions of poor assembly and ambiguity. Fully assembled mitogenomes were then annotated using MITOS 101 by selecting invertebrate mitochondrial genetic code 5. Bed files from MITOS annotations were imported into Geneious 11.1.5 to fine-tune the predicted annotations of gene and protein coding genes (PCGs). All FAW mitogenomes from this study and those from Tay et al. 33 were combined and aligned using MAFFT Alignment v7.450 102,103 within Geneious 11.1.5, using the default Auto option for Algorithm, 1.53 for Gap open penalty 0.123 for offset value, and 200 PAM/K = 2 for Scoring matrix. Once aligned, we trimmed and removed all intergenic regions including the A-T rich replication origin, all tRNAs, and the two rRNA genes, leaving 11,303 bp of the 13 concatenated PCGs. We identified unique concatenated PCG mitogenomes within individual countries using the DNAcollapser in FaBox (1.5) 104 , and partitioned these unique concatenated PCG mitogenomes prior to inferring ML phylogenies without outgroups using IQ-tree implementing UFBoot 94 with 1000 replications to ascertain node confidence. Visualisation and presentation of the phylogeny (Fig. 2) was by Dendrogram 105 to enable a conservative estimate of the number of maternal lineages in the invasive populations. All assembled and annotated mitogenomes used have been deposited in CSIRO public Data Access Portal 106 .
Strain assessment. With the non-recombinant nature of the mitogenomes, we analysed the mitogenomes of the FAW according to their strain classification (i.e., C-strain (corn strain) and the R-strain (rice strain)) separately to identify the conservative number of maternal founders for both strains across the invasive ranges, based on concatenation of the 13 PCG regions only, excluding the tRNA and rRNA genes, and the variable intergenic and AT-rich regions. We follow the naming suggestion of Tay et al. 31 and refer the rice-strain and corn-strain instead as R-strain and C-strain, respectively. Individual FAWs were characterised as the R-or C-strain by comparing their relevant partial mtCOI gene regions against previously characterised reference sequences (rice (R-strain): GenBank MF197867; corn (C-strain): GenBank MF197868; see 22 ). We note that classification of the FAW host-strain (i.e., R-strain/C-strain) is contentious depending on the markers used (e.g., 107 vs. 108 ) and may have limited applications in hybrid populations 31,33 , we nevertheless provided this information based on both the partial mtCOI gene identity and the TPI exon 5 gene region as previously described (i.e., for the TPI loci), to differentiate between the C-strain and R-strain S. frugiperda, whole genome sequence data were mapped to the SFRU_RICE_002481 contig 89 at location 12939.
Principle component analysis (PCA). Principal Component Analysis (PCA) was also carried out to increase interpretability of the large and complex FAW genomic dataset through maximising variance by creating new uncorrelated variables and to aid in visualisation. PCA based on the 870 SNPs was performed using PLINK v1.9 109 and visualised using ggplot2 110  DivMigrate analysis. DivMigrate analysis 111 was carried out using the complete set of 870 SNP loci for all invasive populations from Africa, Asia, and SEA, with the exception of the Kedah State (Malaysia) population that showed unique genomic background (and represented a population from the on-going lab-maintained culture first collected from maize field in 2019). Australia populations representing the 'final arrival' populations, were also excluded in the DivMigrate analysis to increase interpretability relating to East Africa, South Asia, East Asia and SEA populations. Relative migration was assessed using the G ST statistics with 100 bootstrap replications and filter threshold (i.e., visualisation of the number of links in the network plot) was set at 0.453 and plotted using the graph visualisation and manipulation software Gephi 0.9.2 < www. gephi. org > and countries were separately drawn using Microsoft PowerPoint for Mac v16.54.

Data availability
All data used in this study have been deposited in the CSIRO Data Access Portal and are freely accessible, under the permanent links https:// doi. org/ 10. 25919/ 24gy-g132 and https:// doi. org/ 10. 25919/ c53m-ts57.